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“Hot-button” issues in lending: Documentation

Sageworks
May 22, 2012
Read Time: 0 min

John BaptistaGuest post by John Baptista, Impact Training & Consulting

As memberships in U.S. credit unions have grown, many institutions are expanding their offerings to include member business loans. Whether it’s a credit union making this move for the first time, or a bank diving deeper into commercial lending, I find that institutions encounter several common “hot-button” issues associated with commercial lending.

One common “hot-button” issue has to do with handling the documentation associated with commercial loans. This issue arises as early as when the lender begins gathering information from potential borrowers in order to make a solid lending decision – one that’s best for the borrower and for the lender. Commercial lenders must balance customer service issues with the need to have detailed documentation to keep compliance officers and examiners happy.

For example, customers from different generations have different expectations, but you must ensure your approach to documentation ensures true credit analysis. A business owner in his or her 60s or 70s who wants to borrow money might remember “the handshake days” at the bank and still want that experience. Those were the days when your borrower came in, you talked to them, you knew them well enough to strike a deal, and you did the paperwork later.  These customers don’t like hearing words like “policy,” “procedure,” or “we’re required by regulators.”

One CEO I spoke with recently said that in today’s environment, you have to do everything you can to make that customer believe they’re getting the same type of relationship that they had years ago. However, when you’re not around that customer, this CEO said, you need to do everything required in order to ‘dot the I’s and cross the T’s’ of your loan documentation.

So how can you do that? There are three main approaches I’ve seen banks and credit unions I’ve worked with take.

The first is relationship building with your customer. You’ve got to get to know the person you’re dealing with. It’s essential to build a relationship and ask the tough questions so that you have the critical financial information for a proper credit analysis. I always see a customer or potential customer as a jigsaw puzzle. My goal is to find as many pieces of the puzzle as I can.

The second approach is through streamlining and clarifying your application process. I’m a firm believer in checklists.  That way, if someone comes in and is buying a piece of equipment for the business, you have a list that explains what documents they’ll need to provide, depending on the type of business. It’s also important to have checklists that allow co-workers to pick up where one left off. This ensures efficiency and consistency if someone needs to take over or help with that customer.

The third way is through lending software that automates the process. Remember that there are numerous software solutions available to make the credit analysis process easier. The “old school” way of evaluating a loan application was to use a pencil, a spreadsheet, and a calculator to go through tax returns to literally crunch the numbers. Today, credit unions and banks can use software that allows an entry-level clerk or loan assistant to enter the information before the program spreads everything a lender needs to conduct the global analysis.

Of course, you’ve still got to be able to know what the data means. Technology helps, but you still need expertise, and a lot of that comes back to knowing that client.

John Baptista Jr., principal at Impact Training & Consulting, is a national trainer and consultant to the banking industry. He is based in Loveland, Colorado.

About the Author

Sageworks

Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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